mage-ai/mage-ai

Mage OSS is a self-hosted tool for building and running data pipelines. A data pipeline is a sequence of steps that pulls data from one place, transforms or cleans it, and loads it somewhere else. Mage gives you a visual, notebook-style interface to create those steps using Python, SQL, or R, and then connects them together into a pipeline you can run manually or on a schedule. The interface is block-based, meaning you write each step of a pipeline as its own piece of code, preview what the data looks like after each step, and see logs as the pipeline runs. This makes it easier to find where something went wrong without having to trace through a long script. There are prebuilt connectors for common databases, cloud storage services, and APIs so you do not have to write the plumbing yourself. Installation is done with Docker, pip, or conda, and no cloud account is required to get started. You run it on your own machine and have full control over your data. There is also built-in support for dbt, a popular open-source tool for transforming data inside a database, so you can develop and run dbt models from within the same interface. Typical uses include moving data between services (such as from a spreadsheet into a data warehouse), cleaning and aggregating data on a schedule, and building repeatable ETL or ELT workflows locally before deploying them anywhere. The open-source version is the local development environment. The company also offers a paid platform called Mage Pro, which adds team collaboration, AI-assisted development, role-based access, monitoring alerts, and options for managed or on-premises deployment.